Umar Ibrahim Haruna, Muhammad Ahmad, Lin Hang, Hassan Jubril Izge, Cao Rihong
School of Resources and Safety Engineering, Central South University, Changsha 410083, China.
Department of Civil Engineering, Faculty of Engineering, Aliko Dangote University of Science and Technology, Wudil 713101, Kano State, Nigeria.
Materials (Basel). 2025 Apr 9;18(8):1708. doi: 10.3390/ma18081708.
Understanding soil properties' spatial and temporal variability is essential for optimizing road construction and maintenance practices. This study investigates the seasonal variability of soil properties along a 4.8 km roadway in Maiduguri, Nigeria. Using a novel integration of network analysis and geotechnical testing, we analyzed nine soil parameters (e.g., particle size distribution (PSD), Atterberg limits, California bearing ratio) across wet (September 2024) and dry (January 2021) seasons from 25 test stations. Average Atterberg limits (LL: 22.8% wet vs. 17.5% dry; PL: 18.7% wet vs. 14.7% dry; PI: 4.2% wet vs. 2.8% dry; LS: 1.8% wet vs. 2.3% dry), average compaction characteristics (MDD: 1.8 Mg/m wet vs. 2.1 Mg/m dry; OMC: 12.3% wet vs. 10% dry), and average CBR (18.9% wet vs. 27.5% dry) were obtained. Network construction employed z-score standardization and similarity metrics, with multi-threshold analysis ( = 0.05, 0.10, 0.15) revealing critical structural differences. During the wet season, soil networks exhibited a 5.0% reduction in edges (321 to 305) and density decline (1.07 to 1.02) as thresholds tightened, contrasting with dry-season networks retaining 99.38% connectivity (324 to 322 edges) and stable density (0.99). Seasonal shifts in soil classification (A-4(1)/ML wet vs. A-2(1)/SM dry) underscored moisture-driven plasticity changes. The findings highlight critical implications for adaptive road design, emphasizing moisture-resistant materials in wet seasons and optimized compaction in dry periods.
了解土壤性质的时空变异性对于优化道路建设和养护实践至关重要。本研究调查了尼日利亚迈杜古里一条4.8公里长道路沿线土壤性质的季节性变化。通过将网络分析与岩土测试进行新颖整合，我们分析了25个测试站点在雨季（2024年9月）和旱季（2021年1月）的九个土壤参数（例如，粒度分布（PSD）、阿特伯格极限、加州承载比）。获得了平均阿特伯格极限（液限：雨季22.8% 对比旱季17.5%；塑限：雨季18.7% 对比旱季14.7%；塑性指数：雨季4.2% 对比旱季2.8%；液塑比：雨季1.8% 对比旱季2.3%）、平均压实特性（最大干密度：雨季1.8Mg/m对比旱季2.1Mg/m；最佳含水量：雨季12.3% 对比旱季10%）以及平均加州承载比（雨季18.9% 对比旱季27.5%）。网络构建采用z分数标准化和相似性度量，多阈值分析（ = 0.05、0.10、0.15）揭示了关键的结构差异。在雨季，随着阈值收紧，土壤网络的边减少了5.0%（从321条减少到305条）且密度下降（从1.07降至1.02），而旱季网络保持了99.38%的连通性（从324条边到322条边）且密度稳定（0.99）。土壤分类的季节性变化（雨季为A - 4(1)/ML，旱季为A - 2(1)/SM）突出了水分驱动的可塑性变化。研究结果凸显了对适应性道路设计的关键影响，强调在雨季使用耐湿材料以及在旱季进行优化压实。
